In a practical communication network, such as a network employs GSM, CDMA, UMTS or LTE technologies, it is often encountered with a number of cells that malfunction with some kind of fault, due to different causes, including hardware crash, software crash or any algorithm design error. These cells may behave like although these cells run without any alarm from operation and maintenance (O&M) perspective, but no UEs have traffic transfer in them. In this case, before taking serious examination of network infrastructures, which may take quite a long time, an instant solution is to restart these cells as well as sending an alarm to O&M system. This kind of cells are called as sleeping cells and the function of detecting and recovering sleeping cells is called as advanced cell supervision (ACS).
The first and also most critical procedure in ACS function is the operation of detecting the sleeping cell. Specifically, the communication network should be able to distinguish the real sleeping cell and the empty un-loaded cell, both of which observe no traffic transfer in the cell. According to existing solutions, some approaches for detecting a sleeping cell have been proposed. One straightforward approach is to monitor the cell traffic, and once no traffic lasting a sufficient long period appears, this cell may be suspected as a sleeping cell. However, this approach only relies on the previous traffic records but no any hint of current situation, so it leads to high false alarm ratio or long latency because it is difficult to determine how long this period should be set.
Another approach for detecting a sleeping cell is to find some activities which have correlation with traffic in a cell in one period, monitor the traffic happened in the cell if amount of the activities in the period exceeds a threshold, and once no traffic lasting the period appears, this cell may be suspected as a sleeping cell. However, in practice, the load situation for a cell on different moments may vary a lot, e.g., within 24 hours in a day, which may cause the difficulty of setting the value of threshold. On one hand, this threshold should be set small enough so that no real fault is missed with low traffic load; on the other hand, this threshold should be set large enough so that no false alarm is caused by various kinds of disturbing factors. The disturbing factors might appear randomly in cell running, which would lead to a number of traffic-related activities emerging due to these disturbing factors but not the real cell traffic. Some exemplified disturbing factors include noise, interference from neighbor cells, signaling latency, UE radio link failure and UE operation fault. Since the load situation in a cell might vary faster than the threshold is manually configured, the threshold is often not suitable for the specific load situation. In particular, in the case that the threshold is too small, a cell may be incorrectly detected as a sleeping cell due to high disturbing factors; and in the case that the threshold is too large, most sleeping cells may not be detected because the possibility to monitor the traffic happened in the cell is very low.
In view of the foregoing problems, there is a need to find a suitable solution for detecting a sleeping cell, so as to improve detection accuracy for different load situations.